ANALYSIS OF FACTORS AFFECTING THE PROCESSING OF PARAMETRIC INFORMATION DURING THE TESTING AND OBSERVATION OF MILITARY EQUIPMENT

• Yevhen Tertyshnik

  National Defense University of Ukraine

• Volodymyr Cherneha

  National Defense University of Ukraine

• Volodymyr Dzhanazian

  Central Scientific Research Institute of Armament and Military Equipment of the Armed Forces of Ukraine

The article analyzes the conditions, regulatory and applied factors of processing parametric information formed during the testing of weapons and military equipment, with a focus on the specifics of functioning in conditions of large-scale armed aggression. The necessity of integrating modern information technologies into the automation process for data collection and analysis during testing is substantiated. Emphasis is placed on contradictions between existing regulatory requirements and the actual state of the testing process organization, particularly regarding timelines, the number of measured parameters, documentation volume, and the requirements for accuracy and cybersecurity.

The article examines the stages of the life cycle, the main phases of WME testing and the categories of parameters measured during the testing process. It analyzes the experience of testing over 1,200 WME samples conducted in 2024, including UAVs, electronic warfare systems, armored vehicles, small arms, air defense systems and engineering equipment. It is established that under martial law conditions, rapid processing of large volumes of parametric data, along with ensuring data reliability, resilience to external factors and integration into the command and control system, is of critical importance.

A comparative analysis of five modern methodological approaches to data processing is presented: Bayesian methods, deep learning, time series analysis, big data techniques and fuzzy logic. A concept of a hybrid architecture is proposed, enabling the integration of the strengths of each approach according to the tasks of specific testing stages. The use of Bayesian networks and fuzzy logic systems is substantiated as the core of the automated data processing system. Practical recommendations are provided for implementing these approaches in research and testing units of Ukraine’s defense industrial complex.

1. Volodymyr Cherneha , National Defense University of Ukraine

   Candidate of Technical Sciences, Associate Professor

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